1. Field of the Invention
The present invention relates to the rendering of digital image data, and in particular, to the binary or multilevel representation of images for printing or display purposes
2. Background Description
Since images constitute an effective means of communicating information, displaying images should be as convenient as displaying text. However, many display devices, such as laser and ink jet printers, print only in a binary fashion. Furthermore, some image format standards only allow binary images. For example, the WAP1.1 (Wireless Application Protocol) protocol specification allows only for one graphic format, WBMP, a one (1) bit version of the BMP (bitmap) format. Besides allowing only binary images, some image format standards and some displays only allow images of a limited number of pixels. In the WAP 1.1 standard, a WBMP image should not be larger than 150×150 pixels. Some WAP devices have screens that are very limited in terms of the number of pixels. For example, one WAP device has a screen that is 96 pixels wide by 65 pixels high. In order to render a digitized continuous tone input image using a binary output device, the image has to be converted to a binary image.
The process of converting a digitized continuous tone input image to a binary image so that the binary image appears to be a continuous tone image is known as digital halftoning.
In one type of digital halftoning processes, ordered dither digital halftoning, the input digitized continuous tone image is compared, on a pixel by pixel basis, to a threshold taken from a threshold array. Many ordered dither digital halftoning methods suffer from low frequency artifacts. Because the human vision system has greater sensitivity at low frequencies (less than 12 cycles/degree), such low frequency artifacts are very noticeable.
The visibility of low frequency artifacts in ordered dither digital halftoning methods has led to the development of methods producing binary images with a power spectrum having mostly higher frequency content, the so called “blue noise methods”.
The most frequently used “blue noise method” is the error diffusion method. In an error diffusion halftoning system, an input digital image In (the digitized continuous tone input image) is introduced into the system on a pixel by pixel basis, where n represents the input image pixel number. Each input pixel has its corresponding error value En−1, where En−1 is the error value of the previous pixel (n−1), added to the input value In at a summing node, resulting in modified image data. The modified image data, the sum of the input value and the error value of the previous pixel (In+En−1), is passed to a threshold comparator. The modified image data is compared to the constant threshold value T.0, to determine the appropriate output level On. Once the output level On is determined, it is subtracted from the modified image value to produce the input to an error filter. The error filter allocates its input, In−On, to subsequent pixels based upon an appropriate weighting scheme. Various weighting techniques may be used generate the error level E.n for the subsequent input pixel. The cyclical processing of pixels is continued until the end of the input data is reached. (For a more complete description of error diffusion see, for example, “Digital Halftoning”, by Robert Ulichney, MIT Press, Cambridge, Mass. and London, England, 1990, pp. 239-319).
Although the error diffusion method presents an improvement over many ordered dither methods, artifacts are still present. There is an inherent edge enhancement in the error diffusion method. Other known artifacts produced by the error diffusion method include artifacts called “worms” and “snowplowing” which degrade image quality.
In U.S. Pat. No. 5,045,952, Eschbach disclosed selectively modifying the threshold level on a pixel by pixel basis in order to increase or decrease the edge enhancement of the output digital image. The improvements disclosed by Eschbach do not allow the control of the edge enhancement by controlling the high frequency portion of the error. Also, the improvements disclosed by Eschbach do not introduce parameters that can be selected to produce the image of the highest perceptual quality at a specific output device.
In U.S. Pat. No. 5,757,976, Shu disclosed utilizing a set of error filters having different sizes for diffusing the input of the error filter among neighboring pixels in predetermined tonal areas of an image and adding “noise” to the threshold in order to achieve a smooth halftone image quality. The improvements disclosed by Shu do not introduce parameters that can be selected to produce the image of the highest perceptual quality at a specific output device.